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Syllabus |
1. Data Analysis
1.1. Principles and steps.
2. Construction of variables;
2.1. Creation of a database;
2.2. The notion of variable, variable types and scales of measurement;
2.3. Dependent and independent variables;
2.4. Assumptions of parametric and non-parametric tests (Chi-square, Mann-Whitney, McNemar, Wilcoxon, Kruskal-Wallis; Cochran);
2.5. Analysis of the distribution of the data and its implications;
2.6. Control variables;
2.7. Interpretation of results.
3. Data analysis using different software.
4. Review and critical analysis of the scientific literature;
4.1. Structure and fundamental characteristics of a research report;
4.2 Summary of Approach ethical aspects of research and documentary research;
4.3. Quantitative and qualitative methods: differences, limitations and complementarity:
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Main Bibliography |
• Antonius, R. (2013). Interpreting quantitative data with IBM SPSS Statistics. London: SAGE Publications.
• Balnaves, M.E, & Caputi, P. (2001). Introduction to quantitative research methods. An investigative approach. London: SAGE Publications.
• Bazeley, P. (2007). Qualitative data analysis with NVivo. London: Sage Publications.
• Borenstein, M., Hedges, L.V., Higgins, J.P.T., & Rothstein, H.R. (2009). Introduction to meta-analysis. Chichester: John Wiley & Sons, Ltd.
• Cornillon, P.A. (2012). R for Statistics. Boca Raton, FL: Chapman & Hall/CRC Press.
• Denzin, N. K, & Lincoln, Y. S. (2007). The handbook of qualitative research. London: Sage Publications.
• Falissard, B. (2011). Analysis of questionnaire data with R. Boca Raton, FL: Chapman & Hall/CRC Press.
• Frost, N. (2011). Qualitative research methods in psychology. Combining core approaches. UK: McGraw Hill.
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